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Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics

Reply to Comment on “Spectral filters in quantum mechanics: A measurement theory perspective”

Amrendra Vijay

Published Jan 15, 2002• 4 citations
Publisher

Abstract

We address the issues raised in the preceding comment by Mandelshtam and Carrington [Phys. Rev. E 65, 028701 (2002)], concerning the eigenvalue determination by the spectral filter methods. We argue that the Fourier transformation is the building block of all currently known time-domain spectral filter algorithms, and, therefore, the time-energy uncertainty principle affects them all in a similar manner. We also explain the situation when the correlation function method may be less suitable, in comparison to the filter diagonalization method, for the determination of eigenvalues, even though both share the same fundamental principles.

DOI
10.1103/physreve.65.028702

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Spectral filters in quantum mechanics: A measurement theory perspective

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We address the issues raised in the preceding comment by Mandelshtam and Carrington [Phys. Rev. E 65, 028701 (2002)], concerning the eigenvalue determination by the spectral filter methods. We argue that the Fourier transformation is the building block of all currently known time-domain spectral filter algorithms, and, therefore, the time-energy uncertainty principle affects them all in a similar manner. We also explain the situation when the correlation function method may be less suitable, in comparison to the filter diagonalization method, for the determination of eigenvalues, even though both share the same fundamental principles.
We present the time-domain theory of spectral filters, starting with the basic propositions of the theory of measurement in quantum mechanics, and develop its parameter-free implementation in the traditional correlation function as well as the filter diagonalization (FD) form. The present study unifies all the time-domain spectral filter algorithms in the literature, under a single theme which is based on the notion of selective measurements. For specific numerical purposes, we have selected Chebyshev polynomials for developing the time propagator and this permits us to carry out the relevent time integrals fully analytically and obtain FD equations in a numerically convenient form. We also argue that the FD method is a particular realization of the general spectral filter goal and it is constrained, in general, by the time-energy uncertainty regime at least as much as the correlation-function-based method. To contrast the performance of the correlation function and the FD methods, we have carried out the detailed numerical experiments on a model system, which suggest that the FD method needs almost as much time propagation as the correlation function method, in order to identify the correct spectrum. The difference lies in the procedure for the exact location of eigenvalue positions, for which the FD method employs a diagonalization step while the correlation function method involves the location of zeros.
We discuss and clarify the concept of dephasing in the many-Hilbert-space approach to the quantum measurement problem. We argue that the phase randomization provoked by a detecting macroscopic device is responsible for the loss of quantum coherence, and that the ``collapse of the wave function'' is to be regarded as a statistical process for the accumulated distribution over many events. In stressing the fundamental differences between our approach and the Copenhagen interpretation, we counter the objections put forward by Johnston [preceding Comment, Phys. Rev. A 48, 2497 (1993)], whose standpoint is essentially similar to the Copenhagen one.
In a previous paper we developed a method, Filter-Diagonalization, for extracting eigenvalues and eigenstates of a given operator at any desired energy range. In essence, the method eliminates correlation between distant eigenstates through a short-time filter while correlations between closely lying states are eliminated by diagonalization. Here we extend Filter-Diagonalization. When used to extract eigenvalues for a given operator H, we show that all eigenvalue information is directly extracted from a short segment of the correlation function C(t)=(ψ(0)‖e−iHt‖ψ(0)), or alternately from a small number of residues (ψ(0)‖Rn(H)‖ψ(0)), where ψ(0) is a random initial function and Rn(H) is any desired polynomial expansion in H. The implications of this feature are twofold. First, in contrast to the previous version the wave packet needs only to be propagated once (to prepare C(t)), and eigenstates at all desired energy windows can then be extracted with negligible extra computation time (and negligible storage requirements). In a simulation presented here, accurate eigenvalues are extracted using propagation times which are only a 0.0041 fraction of the ‘‘natural’’ time, i.e., the time by which the relative phase of the two closest eigenstates reaches 2π. The second and more important feature is that the method is automatically suitable for extracting eigenvalues (or normal modes) using a short-time segment of any signal C(t) which is a sum of (unknown) Fourier components (C(t)=∑ndne−iεnt) regardless of its origin. In addition to its use for determining eigenvalues of known operators, the method may also be utilized to extract normal modes from classical-dynamics simulations, eigenstates from real-time Quantum Monte-Carlo studies, frequencies from experimental optical or electrical signals, or be utilized in any other circumstance where a correlation function or general signal is only known for short times (or expensive to generate at long times).